A traditional model for electronic-based commerce uses only two parameters to recommend products to users: browsing history and previous purchases. For example, if a user utilized a web browser to both visit a manufacturer's website and purchase a mobile device, the traditional model tracks the visit (browsing history) and the purchase (previous purchases) such that products by that manufacturer related to mobile devices may be recommended to the user via web browser advertisements.
However, success rates for marketing campaigns that utilize this traditional model are low due to generic, unfocused messages that do not match customer needs at the right time. Thus, it would be desirable to provide a system and method that relies upon at least the additional dimension of device activity such as usage patterns to make targeted, timely product and service recommendations.